[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0030112.html
   My bibliography  Save this article

“Hot Hand” on Strike: Bowling Data Indicates Correlation to Recent Past Results, Not Causality

Author

Listed:
  • Gur Yaari
  • Gil David
Abstract
Recently, the “hot hand” phenomenon regained interest due to the availability and accessibility of large scale data sets from the world of sports. In support of common wisdom and in contrast to the original conclusions of the seminal paper about this phenomenon by Gilovich, Vallone and Tversky in 1985, solid evidences were supplied in favor of the existence of this phenomenon in different kinds of data. This came after almost three decades of ongoing debates whether the “hot hand” phenomenon in sport is real or just a mis-perception of human subjects of completely random patterns present in reality. However, although this phenomenon was shown to exist in different sports data including basketball free throws and bowling strike rates, a somehow deeper question remained unanswered: are these non random patterns results of causal, short term, feedback mechanisms or simply time fluctuations of athletes performance. In this paper, we analyze large amounts of data from the Professional Bowling Association(PBA). We studied the results of the top 100 players in terms of the number of available records (summed into more than 450,000 frames). By using permutation approach and dividing the analysis into different aggregation levels we were able to supply evidence for the existence of the “hot hand” phenomenon in the data, in agreement with previous studies. Moreover, by using this approach, we were able to demonstrate that there are, indeed, significant fluctuations from game to game for the same player but there is no clustering of successes (strikes) and failures (non strikes) within each game. Thus we were lead to the conclusion that bowling results show correlation to recent past results but they are not influenced by them in a causal manner.

Suggested Citation

  • Gur Yaari & Gil David, 2012. "“Hot Hand” on Strike: Bowling Data Indicates Correlation to Recent Past Results, Not Causality," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-9, January.
    • Handle: RePEc:plo:pone00:0030112
    DOI: 10.1371/journal.pone.0030112
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030112
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0030112&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0030112?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jordi Duch & Joshua S Waitzman & Luís A Nunes Amaral, 2010. "Quantifying the Performance of Individual Players in a Team Activity," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-7, June.
    2. Arkes Jeremy, 2010. "Revisiting the Hot Hand Theory with Free Throw Data in a Multivariate Framework," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-12, January.
    3. C. Sire & S. Redner, 2009. "Understanding baseball team standings and streaks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 473-481, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joshua B. Miller & Adam Sanjurjo, 2014. "A Cold Shower for the Hot Hand Fallacy," Working Papers 518, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    2. Gur Yaari & Shmuel Eisenmann, 2011. "The Hot (Invisible?) Hand: Can Time Sequence Patterns of Success/Failure in Sports Be Modeled as Repeated Random Independent Trials?," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-10, October.
    3. Arkes Jeremy & Martinez Jose, 2011. "Finally, Evidence for a Momentum Effect in the NBA," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-16, July.
    4. Filippo Radicchi, 2011. "Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-7, February.
    5. Mukherjee, Satyam, 2012. "Identifying the greatest team and captain—A complex network approach to cricket matches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6066-6076.
    6. Gabel Alan & Redner Sidney, 2012. "Random Walk Picture of Basketball Scoring," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-20, March.
    7. Brander James A. & Egan Edward J. & Yeung Louisa, 2014. "Estimating the effects of age on NHL player performance," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(2), pages 241-259, June.
    8. Joshua B. Miller & Adam Sanjurjo, 2015. "Is it a Fallacy to Believe in the Hot Hand in the NBA Three-Point Contest?," Working Papers 548, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Craig A. Depken II & Matthew Hood & Ernest King, 2017. "Consistency and Momentum in NASCAR," Journal of Sports Economics, , vol. 18(6), pages 601-621, August.
    10. Tomás Rodríguez & Jorge Tovar, 2023. "The hedgehog or the fox: Versatility and performance in professional soccer," Documentos CEDE 20757, Universidad de los Andes, Facultad de Economía, CEDE.
    11. Joshua B. Miller & Adam Sanjurjo, 2014. "A Cold Shower for the Hot Hand Fallacy," Working Papers 518, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    12. Ichinose, Genki & Tsuchiya, Tomohiro & Watanabe, Shunsuke, 2021. "Robustness of football passing networks against continuous node and link removals," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    13. António Sérgio Ribeiro & Francisco Lima & Sascha Kraus & Ferran Calabuig, 2022. "Tournaments within football teams: players’ performance and wages," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 4884-4901, December.
    14. Robert M. Lantis & Erik T. Nesson, 2019. "Hot Shots: An Analysis of the ‘Hot Hand’ in NBA Field Goal and Free Throw Shooting," NBER Working Papers 26510, National Bureau of Economic Research, Inc.
    15. Peter Csapo & Markus Raab, 2014. "“Hand down, Man down.” Analysis of Defensive Adjustments in Response to the Hot Hand in Basketball Using Novel Defense Metrics," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-25, December.
    16. Rubén Maneiro & Claudio A Casal & Antonio Ardá & José Luís Losada, 2019. "Application of multivariant decision tree technique in high performance football: The female and male corner kick," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.
    17. Albert Cohen & Jimmy Risk, 2023. "European Football Player Valuation: Integrating Financial Models and Network Theory," Papers 2312.16179, arXiv.org, revised Oct 2024.
    18. Wu, Yao & Xia, Zeyu & Wu, Tian & Yi, Qing & Yu, Runyu & Wang, Jun, 2020. "Characteristics and optimization of core local network: Big data analysis of football matches," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    19. Joshua B. Miller & Adam Sanjurjo, 2018. "Surprised by the Hot Hand Fallacy? A Truth in the Law of Small Numbers," Econometrica, Econometric Society, vol. 86(6), pages 2019-2047, November.
    20. Meier, Philippe & Flepp, Raphael & Ruedisser, Maximilian & Franck, Egon, 2020. "Separating psychological momentum from strategic momentum: Evidence from men’s professional tennis," Journal of Economic Psychology, Elsevier, vol. 78(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0030112. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.